Determining Repulsion in Cyclophane Cages

Abstract

Superphane, i.e., [2.2.2.2.2.2](1,2,3,4,5,6)cyclophane, is a very convenient molecule in studying the nature of guest⋯host interactions in endohedral complexes. Nevertheless, the presence of as many as six ethylene bridges in the superphane molecule makes it practically impossible for the trapped entity to escape out of the superphane cage. Thus, in this article, I have implemented the idea of using the superphane derivatives with a reduced number of ethylene linkers, which leads to the [2n] cyclophanes where n<6. Seven such cyclophanes are then allowed to form endohedral complexes with noble gas (Ng) atoms (He, Ne, Ar, Kr). It is shown that in the vast majority of cases, the initially trapped Ng atom spontaneously escapes from the cyclophane cage, creating an exohedral complex. This is the best proof that the Ng⋯cyclophane interaction in endohedral complexes is indeed highly repulsive, i.e., destabilizing. Apart from the ‘sealed’ superphane molecule, endohedral complexes are only formed in the case of the smallest He atom. However, it has been shown that in these cases, the Ng⋯cyclophane interaction inside the cyclophane cage is nonbonding, i.e., repulsive. This highly energetically unfavorable effect causes the cyclophane molecule to ‘swell’.

A Review of Crystalline Multibridged Cyclophane Cages: Synthesis, Their Conformational Behavior, and Properties

“…For example, a multiple-bridged cyclophane cage consisting of benzene rings and positively charged imidazole rings can form a cavity that encapsulates some suitably sized anions. Outside the cavity, the nests formed between the imidazole rings can also be used to selectively bind the molecule to anionic or neutral molecules by electrostatic action and cationic–π interaction; whereas inserting a noble gas (Ng) atom into the cavity of the superphane molecule [2.2.2.2.2.2](1,2,3,4,5,6)cyclophane with six flexible ethylene bridges may lead to the formation of a Ng@superphane endohedral complex and the corresponding significant “swelling”, which is mainly manifested by increasing the distance between benzene rings [ 73 ].…”

Unveiling the Noncovalent Interaction of Thiazol‐2‐ylidene and Its Derivatives as N‐heterocyclic Carbene with Different Proton Donor Molecules

“…In general, among the five proton donor molecules, HF and HCN form a linear H-bonding interaction with carbene. [25] But due to the unsymmetrical nature of the thiazol-2-ylidene carbene, the bond angle value deviates from the ideal 180°to 170.52°and 175.70°for angles ffCÀ H-F and ffCÀ H-CN, respectively. HF forms a very strong interaction with the parent carbene.…”

“…All the molecular geometries, including carbenes, hydrogen donor molecules, and their complexes, were optimized using dispersion-corrected functionals ωB97XD [66,67] and B3LYP-D3 [68][69][70] with 6-311 + + G(d,p) basis set. [25,69] It is well established that D3-Grimme's dispersion correction is essential for investigating systems with noncovalent interactions. [71][72][73] Further, to confirm the energy minima, vibrational frequency analysis has been carried out at the same level of theory using Gaussian 16 program package.…”

“…At the outset, the interaction of carbene with transition metal [2,[19][20][21] produced highly valuable complexes in organic, material, and organo-metallic chemistry. [2,3,6] In addition, carbene also engages with other intermolecular interactions such as hydrogen bonds, [16,[22][23][24][25][26] halogen bonds, [26][27][28][29][30][31] beryllium bonds, [8,[32][33][34][35] lithium bonds, [8,29,[36][37][38] triel bonds, [29,[39][40][41][42] magnesium bonds, [34,35,[43][44][45] chalcogen bonds, [46] and aerogen bonds. [47] These interactions occur due to a lone pair of electrons in the carbene carbon atom.…”

Testing of Exchange-Correlation Functionals of DFT for a Reliable Description of the Electron Density Distribution in Organic Molecules

“…Unfortunately, one could say that at present there are as many exchange-correlation functionals as ants in an anthill, which leads to the situation that we currently have hundreds of them, and choosing the most appropriate one for a given problem is one of the biggest concerns when using DFT. Therefore, benchmark calculations in which the reliability of DFT functionals is tested are extremely important [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 ]. However, the bottleneck here is the enormous amount of calculations to be made.…”